Model of Defensive Information Avoidance
A Model of Defensive Information Avoidance in Information Systems Use Research-in-Progress
Tillmann Neben University of Mannheim Mannheim, Germany
[email protected] This paper looks at defensive information avoidance: the phenomenon that users avoid decision-relevant but incongruent information. Since only utilized information can contribute to better decision-making, the phenomenon of information avoidance is of great relevance to the information systems discipline. This paper contributes the first coherent conceptualization of information avoidance behavior by synthesizing scattered but related definitions. Building on this, it proposes a theoretical model and explains how encountering decision-relevant but incongruent information relates to different avoidance behaviors. In particular, it helps to understand yet unexplained IS use phenomena, where encountering incongruent information – paradoxically – leads to a higher information exposure but a decreased information absorption and use. The paper contributes methodologically by proposing a series of neurophysiological measures for testing the explanatory model. It derives and discusses two experimental paradigms from experimental psychology for testing the hypothesized effects. Keywords: Information avoidance, information pathologies, NeuroIS
Introduction This paper investigates why users avoid decision-relevant information. It explains how incongruent information leads to the perception of dissonance and to defensive avoidance reactions. Information is incongruent if it mismatches prior beliefs, decisions, or knowledge. The effects of incongruence and dissonance on user behavior are relevant to information systems (IS) research for two reasons. First, past research has focused on syntactic and semantic information characteristics and their effect on cognitive load (Huang 2000; Jacoby 1984) but little is known about how deficits on the pragmatic level of information relate to negative affect and changes in human information processing (Bawden and Robinson 2008; Nahl and Bilal 2007). Second, because the chance of encountering incongruent information increases with the constantly growing amount of available information, understanding how information characteristics affect information behaviors is of increasing relevance (Floridi 2009). The study, thus, relates to recent research on user behavior and effective use (Burton-Jones and Grange 2013; Pavlou et al. 2008). However, it is original because its dependent variable is not decision efficiency and quality, but pathologies in information processing. This is grounded in the insight that information needs to be processed before it can affect decision quality (Witte et al. 1972), or in a broader sense, affect IS phenomena, such as knowledge management, information management, or organizational learning. In other words, users that avoid relevant information are less likely to make optimal decisions. This paper proposes a model of defensive information avoidance. In order to do this, it investigates changes in human behavior in response to encountering unpleasant or threatening information. Past research on information avoidance is scattered and no unified conceptualization of information avoidance exists. Various researchers define it as the avoidance of reading (Bodenhausen and Wyer 1987; Guo et al. 2005), search (Bhatia 2014; Hong 2014), usage (Diamantopoulos and Souchon 1999), or sharing
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Model of Defensive Information Avoidance
(Connelly et al. 2012) of information. However, a clear-cut definition of the construct is a prerequisite for theorizing its explanation. Thus, the first research question for this paper is: RQ1: How can information avoidance behavior be conceptualized and what specific subtypes of avoidance behaviors exist? This paper wants to explain how information characteristics cause defensive avoidance reactions. Past research has not explained which characteristics of the information relate to defensive avoidance behaviors. Accordingly, and following Floridi’s (2009) call for investigating how information characteristics relate to human behaviors, the second research question is: RQ2: Which information characteristics relate to defensive information avoidance behaviors? Since past studies present contradicting explanations for defensive avoidance behaviors, this paper unifies a wide range of psychological theories into a coherent model. The third research question is: RQ3: What are the psychological explanations for defensive avoidance behaviors?
Literature Review To study misguided and dysfunctional information behaviors, past research established the notion of information pathologies (Scholl 2004; Selke 2006) and biases (Tversky and Kahneman, 1973). They describe behaviors that result in relevant information not being shared, read, or used (Scholl 2004; Selke 2006; similar see Browne et al. 2007). The literature reveals a dichotomy of the underlying causes of information avoidance: on the one hand, psychological explanations are based on the perception of fear, anger, doubt, and anxiety. These explanations are based on the idea that a particular piece of information is perceived as a threat (Jonas et al. 2001). On the other hand, psychological explanations are based on the concept of mental overload. These explanations relate to the idea that a particular piece of information causes increased mental effort (Malhotra et al. 1982). While reference disciplines such as psychology have a cumulative research tradition concerning related phenomena, the IS discipline lacks systematic research where avoidance of information is the dependent variable (Neben et al. 2013; similar see Hemmer and Heinzl 2011). Reviewing the reference disciplines revealed that only a few studies have looked at information avoidance in a holistic manner and have considered different causes, in addition to different manifestations of the avoidance phenomenon (Wang and Domas 1999; Melnyk 2009; Sweeny et al. 2010; Sweeny and Miller 2012). Most studies focus on specific aspects of the phenomenon (Howell and Shepperd 2012) or specific behaviors, such as the avoidance of searching or the avoidance of articulating an information need (Case et al. 2005). A broad research stream is concerned with selective exposure, which relates to behaviors aimed at preventing confrontation with specific information (Cotton and Hieser 1980; Fischer and Greitemeyer 2010; Fischer, Schulz-Hardt, et al. 2008; Garrett 2013; Kastenmüller et al. 2013; KnoblochWesterwick and Meng 2009; Sears and Freedman 1967). Other studies are concerned with the subtypes of use avoidance (Choo et al. 2008; Greenwald 1997; Menon and Varadarajan 1992; Narayan et al. 2011) or the avoidance of adequate information absorption (Beevers and Scott 2001; Bodenhausen and Wyer 1987; Guo et al. 2005). Confirmatory search refers to a search for supporting information after making a decision (Scherer et al. 2013). Theoretically, this is different from the concept of selective exposure, which does not describe the information search, but the information selection (Fischer et al. 2005). However, several studies diverge from this definition and include the notion of active search in their conceptualization of selective exposure (Valentino et al. 2009). Information non-use involves preventing the information from actively and purposefully leading to specific decisions, actions, or thoughts (Dervin 1998; Greenwald 1997; Todd 1999). Blunting refers to avoidance reactions when stumbling over information that is perceived negatively (Sexton and Dugas 2008; Van Zuuren and Wolfs 1991). A frequently cited definition of information avoidance is based on the work of Sweeny et al. (2010) which defines information avoidance as any behavior directed at preventing or delaying the acquisition of available but potentially unwanted information. Interestingly, this definition does not require the information to be useful and decision-relevant. However, in order to distinguish information avoidance behavior from related phenomena, such as lack of interest, time pressure, and economically sound
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Model of Defensive Information Avoidance
behaviors, such as the avoidance of irrelevant information (Poulsen and Roos 2010), some researchers require the avoided information to be decision-relevant (Narayan et al. 2011; Scholl 2004). Furthermore, the definition refers to information acquisition, but omits other potentially relevant information behaviors, such as information use (Melnyk 2009). Since the literature is inconsistent concerning the conceptualization and delineation of the phenomenon, it remains inconclusive in explaining the involved psychological processes and their relation to information, tasks, and system characteristics. Most studies explicitly or implicitly build on coping theory and the notion that a stimulus goes through several phases of appraisal (Roth and Cohen 1986; Smith and Lazarus 1993). Explanations that relate to defensive information avoidance are often grounded in theories of cognitive dissonance, ego-defense, and anxiety. Several moderators have been discussed, for example, differences in personality (Hart et al. 2012; Miller 1987), different coping styles, and personal uncertainty orientation (Brouwers and Sorrentino 1993; Sorrentino et al. 1988; 1995). Other scholars have discussed the moderators mood, self-esteem (Wiersema et al. 2012), and situational and task characteristics (Scholl 2004; Sweeny et al. 2010).
Development of a Theoretical Model Deriving a Conceptualization of Information Avoidance Behavior A coherent conceptualization of the information avoidance construct is a prerequisite for explaining and predicting information avoidance behavior. The literature review has revealed that no such conceptualization yet exists. To answer research question 1, this paper proposes a conceptualization that is based on idealized information behavior processes derived from the literature on human information behavior (Dervin 1998; Nahl and Bilal 2007; Savolainen 1993; 2007; Wilson 1999; 2000). It subdivides information processing into the abstract phases of exposure, absorption, and use. Exposure refers to either actively seeking contact with a piece of information or allowing contact when passively exposed to it, for example, paying attention to a link “read more” and clicking it. Absorption refers to the act of actually consuming and processing the information, for example, through reading or listening. Use refers to the transformative process of shaping decisions using the information. Because information avoidance can occur during each phase, the construct is split into three sub-constructs: exposure avoidance, absorption avoidance, and use avoidance. Exposure avoidance refers to either actively or passively preventing contact with information (Fischer et al. 2005). Active selective exposure refers to avoiding searching, and passive selective exposure refers to avoiding learning that information (in principle) exists. Absorption avoidance refers to information being processed with a lower intensity or not at all. An example is purposeful superficial reading or skimming (Donohew et al. 1972; Maier and Richter 2013). Use avoidance refers to preventing the transformative process of shaping decisions using the information (Choo et al. 2008; Dervin 1998; Greenwald 1997; Menon and Varadarajan 1992). An example is the avoidance of drawing inferences from obtained information (Greenberg et al. 2003). Building on this integration of constructs and the definition by Sweeny et al. (2010) and by focusing on decision-relevant information (Narayan et al. 2011; Scholl 2004; Shanteau 1992), information avoidance is defined as limiting or terminating the attention given to cues that indicate that decision-relevant information is available, or limiting or terminating the search for decision-relevant information (exposure avoidance), limiting or terminating the absorption of decisionrelevant information (absorption avoidance), and limiting or terminating the use of decision-relevant information (use avoidance). Table 1 depicts how the scattered literature on separate subtypes of information avoidance are integrated into the idealized search process and the three sub-constructs.
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Model of Defensive Information Avoidance
Table 1: Phenomena Evident in the Literature “Confirmatory Search”
“Selective Exposure”
“Superficial processing”
“Information non-use”
Bhatia 2014; Fischer et al. 2011; McIntosh et al. 2001; Phillips et al. 2008; Shepherd et al. 2012; Swann and Giuliano 1987
Case et al. 2005; Donohew et al. 1972; Howell and Shepperd 2012; Maier and Richter 2013; Melnyk 2009; Miles et al. 2008; Mills and Jellison 1968
Beevers and Scott 2001; Bodenhausen and Wyer 1987; Guo et al. 2005; Ingram 1984; Johnson 2005; Osvaldo De Sordi et al. 2014
Choo et al. 2008; Greenwald 1997; Menon and Varadarajan 1992; Narayan et al. 2011; Shanteau 1992; Wang and Domas 1999; Wang and Soergel 1998
Integrated into idealized process of information behavior: Exposure Avoidance à
Absorption Avoidance à
Use Avoidance
Limiting or terminating the search for decision-relevant information
Limiting or terminating the absorption of decision-relevant information
Limiting or terminating the use of decision-relevant information
Understanding the Role of Approach and Defense Motivations in Information Avoidance Behavior This paper is concerned with defensive information avoidance. For explaining avoidance, it is necessary to understand what causes information approach. Based on the theory of motivated reasoning (Kunda 1990), this paper proposes that two simultaneous and competing motivational forces are prevalent when individuals encounter information. Approach motivation (Kunda 1990; Munro and Stansbury 2009) describes the desire to steer mental resources towards information exposure, absorption, and use. This is based on the information’s perceived usefulness for solving a task. Perceived usefulness of information is theoretically linked to its topicality and quality (Richard et al. 1996; Wang and Soergel 1998). Information is topical if it relates to the concepts and rules relevant to solving the task (BoYcE 1982; Hjørland 2001). Information quality is determined by the absence of the intrinsic quality deficits of ambiguity, inconsistency, vagueness, imprecision, and redundancy (Boell and Cecez-Kecmanovic 2010; Lee et al. 2002; McKinney and Yoos 2010; Stvilia et al. 2007). Information that is seen as potentially useful represents an opportunity and motivates its absorption, exposure, and use (White et al. 2003). The anticipation of positive affect resulting from anticipated information usefulness causes approach motivation (Richard et al. 1996). It follows from the theory of planned behavior that positive outcome expectancies lead to higher use intentions (Madden et al. 1992). In line with the theory of planned behavior, it is predicted that positive outcome expectancies lead to higher use intentions and to actual use (Madden et al. 1992; Menon and Varadarajan 1992) Defense motivation (Kunda 1990; Munro and Stansbury 2009; Sherman and Cohen 2002; 2006) describes the desire to steer mental resources away from information exposure, absorption, and use. This is based on the information’s capacity to pose a threat, where threat does not refer to a physical threat, but to the anticipation of a negative affect arising from the information’s pragmatic implications (Sherman and Cohen 2002). Threat is a future-oriented cognitive-affective state (Gray and McNaughton 2003) and primarily determined by the anticipation of events. Most psychological threats relate to the self and selfperception in relation to the environment (Das and Fennis 2008; Festinger 1962; Proulx et al. 2012). Encountering information that mismatches what is expected and believed challenges one’s perception of the self and the environment (Proulx et al. 2012). Researchers studied various manifestations of what
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specifically can mismatch: new information can mismatch, for example, with prior beliefs, social status perception, or past decisions (Bonniot-Cabanac et al. 2012; Fontanari et al. 2011). All these manifestations represent instances of information incongruence. While information quality refers to intrinsic information characteristics, information congruency refers to the pragmatic compatibility between units of information (Proulx et al. 2012; Taber and Lodge 2006). Accordingly, incongruence refers to the pragmatic disagreement and incompatibility between units of information. The consequence of incongruence is dissonance, and dissonance stands in relationship to defense motivations (Cooper and Worchel 1970; Festinger 1962; Harmon-Jones and Harmon-Jones 2002; Jones and Amodio 2009; Zajonc 1960). However, past research is inconclusive concerning the actual behavioral results of this defense motivation. It reports both approach as well as avoidance behaviors, and posits that the assumption of defense motivations always leading to avoidance reactions (Lowin 1967) is not true (Cotton and Hieser 1980; Mills 1965; Sears and Freedman 1967). Specifically, there is evidence that incongruent information receives increased initial attention (Jang 2014).
Research Model and Hypotheses The following section derives a theoretical explanation for the relationships between information incongruence, threat, and defense motivations in situations of information encountering. It explains why defense motivations cause increased initial information exposure, but subsequently decreased information absorption and use. The model is depicted in Figure 1.
Figure 1. Research Model
Based on extant theory, this paper posits that the need to perceive and assess the threat causes a higher initial exposure, but that the desire to reduce dissonance and to circumvent the unpleasant information reduces the intensity of actual information absorption and use. The following section articulates and explains the hypotheses of the model. Table 2 provides the definitions of all theoretical constructs that are part of the model.
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Table 2. Construct Definitions
Mediators
DVs
Construct
Definition
Based on
Information Avoidance
Limiting or terminating the exposure to, absorption of, or use of decision-relevant information
Sweeny et al. 2010; 2012
- Exposure
Searching for or opening the information
Rieh 2002
- Absorption
Taking-in the information through one’s senses – e.g. through reading.
Dervin 1998; Wilson 2000
- Use
The transformative act of shaping decision through Information (cues)
Choo et al. 2008; Menon and Varadarajan 1992; Shanteau 1992; Wang and Domas 1999
Anticipated information threat
Expectation that the information has the potential to cause negative affect
Gray and McNaughton 2003; Richard et al. 1996
Defense motivation
Motivational state of preparing cognitive and affective resources
Kunda 1990; Munro and Stansbury 2009; Masterson and Crawford 1982
The information’s pragmatic disagreement and incompatibility with another piece of information
Meffert et al. 2006; Taber and Lodge 2006
IVs
Information - Incongruence
New information is perceived as incongruent if it stands in pragmatic disagreement to prior beliefs or knowledge (Taber and Lodge 2006). Pragmatism refers to drawing meaning inferences from the information (Harris and Monaco 1978). Thus, incongruence implies the presence of at least two discrepant cognitions (Jones and Amodio 2009), namely the existing knowledge and the meaning inferred from the new (incongruent) information. Holding discrepant cognitions is linked to perceiving dissonance (Fischer and Greitemeyer 2010; Fischer, Kastenmüller, et al. 2011). If the challenged beliefs and knowledge are of self-relevance, the result is the perception of threat (Proulx et al. 2012; Sherman and Cohen 2002). Accordingly, it is predicted that high incongruence leads to high threat perception: H1: The higher the information incongruence to existing beliefs and knowledge, the higher the perceived threat by the information. Perceiving threat causes complex cognitive and affective processes (Bawden and Robinson 2008; Cheikes et al. 2004; Kuhlmann 1983; Scherer 2000). Psychologically, the perception of a threat is linked to the activation of defense motivations. Defense motivations refer to the preparation of cognitive affective resources in order to cope with the stimulus (Masterson and Crawford 1982). Assessing available resources is a prerequisite for comparing available resources to required recourses as predicted by coping theory during primary appraisal (Folkman 1984). Accordingly, it is hypothesized that: H2: The higher the perceived information threat, the higher the defense motivation. Being exposed to incongruent and thus threatening information is a stressful event. Coping theory posits that contact with a stressful event causes a cognitive appraisal process (Folkman and Lazarus 1988; Krohne 2001; Lazarus 1993; Schwarzer and Schwarzer 1996; Weinert et al. 2013). This process aims at assessing the stressor and determining coping resources for mastering or reducing the demands created by the stressor. This requires that attention be placed on the stimulus. Accordingly, individuals will place initial attention (Meffert et al. 2006) on the stimulus that “captures the interest” (Meffert et al. 2006, p. 28) as part of an initial action orientation (Jones and Amodio 2009). This is also supported from an evolutionary standpoint and by the orienting response (Bernstein 1979): the initial approach to a threat allows the selection of appropriate actions (Roth and Cohen 1986). Accordingly, it is hypothesized: H3: The higher the defense motivation, the more intense the exposure to the information.
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Several studies have linked defense motivations to absorption and use avoidance (Brannon et al. 2007; Case et al. 2005; Fischer and Greitemeyer 2010; Knobloch-Westerwick and Jingbo Meng 2009; Krohne and Hock 2011). This is explained by the desire to reduce dissonance and to resolve the associated negative affect. Stopping to absorb the information or absorbing the information only superficially (e.g. by skimming) allows increasing the distance between oneself and the information. Similarly, not using the information and not integrating it into one’s mental model allows increasing the distance between oneself and the information (Diamantopoulos and Souchon 1999; Garrett 2009). In line with this, it is hypothesized that: H4: The higher the defense motivation, the less intense the absorption of the information. H5: The higher the defense motivation, the less intense the use of the information. In summary, the research model predicts that information incongruence causes dissonance and the perception of threat. This threat causes a defense motivation that has complex effects on the actual outcome behavior. The more incongruent the information a user encounters, the higher the willingness to seek exposure, but the less intense the information absorption and the lower the actual information use.
Research Design This paper proposes adopting an experimental research design (Benbasat and Schroeder 1977; Benbasat and Taylor 1982) for testing the research model. The range of research methods within the experimental methodology is vast. Recent advances in NeuroIS have introduced methods that allow researchers to elicit neuro- and psychophysiological data for providing empirical evidence (Loos et al. 2010; Riedl et al. 2012). For reducing common method bias, this paper seeks to triangulate several measurement instruments (Burton-Jones 2009; Burton-Jones and Straub 2004). The following section outlines the planned experiments, the construct operationalizations, and the method choices.
Tasks and Stimuli There are two paradigms in experimental psychology for studying the effects of incongruence, dissonance, and threat, and they differ in how they manipulate threat. The first paradigm creates threat by presenting a choice scenario and requires participants (Ps) to make a preliminary decision. Additional information is presented after the decision. Depending on the choice, some information will be perceived as congruent and some as incongruent. The second paradigm makes use of Ps predispositions concerning a topic; researchers frequently select polarizing topics, such as abortion or gun laws. This paper seeks to test the hypothesized research model in two experiments. The first experiment represents the first paradigm and is an extension of the Mr. Miller task scenario from psychology (Fischer et al. 2008; Niedernhuber et al. 2014). Ps are assigned the role of HR managers who have to make a decision on the termination or extension of the contract of the employee Mr. Miller. After Ps made a preliminary decision about Mr. Miller’s future, several opinion pieces about Mr. Miller’s performance are presented. These texts are presented as a list of excerpts and speak either in favor of or against Mr. Miller. They are perceived as either congruent or incongruent – depending on the subject’s preliminary decision. Ps can request full texts by selecting individual excerpts (exposure) and read the documents (absorption). In the last stage of the experiment, Ps make a final decision concerning Mr. Miller (use). The paper’s second experiment represents the second paradigm. This paradigm makes use of Ps existing attitudes. A pretest (n=50) identified nuclear energy as a polarizing topic among the target (student) population. Eight pronuclear and eight antinuclear texts of similar complexity and length have been created and validated in another pretest (n=80). Depending on Ps’ existing attitudes (for or against nuclear power), half of the texts will be perceived as congruent and the other half incongruent. The experimental task then follows the Mr. Miller scenario described above.
Measurements This paper proposes combining neurophysiological measures with self-rating scales and observations. Because participants may perform poorly in reporting perceived levels of threat accurately, the introduction of neurophysiological measures is promising. The following introduces the neurophysiological measurement of threat, information exposure, and information absorption. Threat is
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similar to stress in causing a (bodily) physiological activation. Threat is not an emotion, however it cooccurs with emotions such as anxiety, doubt, frustration, and anger (Tomaka et al. 1993). It is possible to measure threat by observing the physiological activation itself or by observing the negative emotions that correlate with threat. This paper combines both approaches by using electrodermal activity (EDA) and pulse plethysmography (PPG) for measuring physiological arousal (Adam et al. 2011; Carbonnell et al. 2006; Cooper and Croyle 2007), and using facial electromyography (fEMG) for detecting expressive correlates of negative emotion. EDA measures changes in the electrical properties of the skin that reflect activation of the autonomous nervous system. Electrodes are attached to participants non-dominant hand (Christie 1981). PPG measures blood flow and heart rate using infrared light (Carter et al. 2005). The PPG sensor is places on participants’ non-dominant index finger. Facial EMG measures the electrical activation of facial muscles. Emotional perceptions are reflected in facial muscle activation (van Boxtel 2009). These can be minimal, unconscious, and invisible for the human eye. Relevant for measuring negative emotions is the corrugator supercilii (“frowning”) muscle that is responsible for eye brow movement (van Boxtel 2009). Eye-tracking allows recording eye-movements (saccades) and fixations, and thus making inferences about attention and information processing (Cyr et al. 2009; Granka et al. 2008; Hermens and Walker 2012). Previous work used eye-tracking for measuring intra-individual differences in reading behavior and reading intensity (Holsanova 2006; Rayner 2009; Rayner et al. 2006). This paper uses eye-tracking for measuring information exposure and absorption. This paper uses scales for measuring anticipated information threat (based on MacLeod and Hagan (1992) and Speilberger and Vagg (1984)), defense motivation (based on Folkman (2013), Miller (1987) and Vitaliano et al. (1985)), and information use (based on (Diamantopoulos and Souchon 1999; Maier and Richter 2013)). All items are 7-point Likerttype scales anchored at agree and disagree.
Discussion and Conclusion This research-in-progress seeks to contribute in four ways: first, it provides a unified conceptualization of information avoidance behavior. Providing this first conceptualization draws attention to the phenomenon of information avoidance, and allows future research to approach the phenomenon in a structured way. Second, it offers a theoretical model for explaining yet unexplained IS use phenomena, where decision-relevant but incongruent information – paradoxically – leads to a higher exposure but a decreased absorption and use. Third, it proposes a series of neurophysiological measures that rely on fEMG, PPG, EDA, and eye-tracking. Conducting the full experiment will provide further insights into their validity and reliability, and could potentially manifest a methodological contribution. Fourth, this paper presents two experimental paradigms derived from experimental psychology for studying information avoidance behavior. IS researchers interested in information avoidance – or information pathologies in general – are invited to build on these paradigms when conducting their experiments. The paper contributes to practice, by explaining how users that avoid decision-relevant information are less likely to make optimal decisions. Based on the model, practitioners can understand that defense motivations cause information avoidance and that interventions aiming at overcoming information avoidance would need to address this defensive reaction first.
Limitations Because of the research-in-progress status, several limitations exist. The current model (Figure 1) looks at situations of information encountering, which is a form of passive information exposure (see active versus passive exposure). It thus describes situations where a person “stumbles” over e.g. a document and decides to open it (exposure), read the content (absorption), and draw inferences from its information (use). This passiveness is also evident in the two described experimental paradigms. Hypothesis 3 thus reflects the willingness for exposure after such passive encounters. Future versions of the model may be extended to account for situations of active exposure – such as information search. This research-inprogress discussed a series of moderators. However, in order to concentrate on the core of the threatbased explanations of information avoidance, these moderators are not part of the depicted model (Figure 1). Future versions of the model could be extended to include these moderators.
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